A new approach for finding an appropriate combination of texture parameters for classification

This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

Small and medium enterprises’ solution to improve on-site waste management in office building retrofit projects

Office building retrofit projects are increasingly more intensified as existing buildings are aging. At the same time, building owners and occupants are looking for environmentally sustainable products. These retrofit projects usually take place in center business district (CBDs) with on-site waste becoming one of the critical issues. Small and Medium Enterprises (SMEs) carry out most of the work in retrofit projects as subcontractors. Despite their large involvement, they often do not have adequate resources to deal with the specific technical challenges and project risks related to waste. Few research has been done on their performance of waste management operations. This paper identifies characteristics of on-site waste in office building retrofit projects. It examines the specific requirements for contractors to manage waste in the projects before exploring the existing performance of SMEs. By comparing requirements for SMEs and their potential areas for improvement, a framework is established for performance promotion of SMEs in on-site waste management of office building retrofit projects. The paper will raise the consciousness and commitment of SMEs as sub-contractors to waste management. It also explores ways of supporting SMEs for experience accumulation, performance promotion and project culture establishment towards effective and efficient on-site waste management in the growing sector of office building retrofit and upgrade.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors

This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

Inter-and Intra-Site Genetic Diversity of Natural Field Populations of Rice Tungro Bacilliform Virus in the Philippines

The genetic structure of rice tungro bacilliform virus (RTBV) populations within and between growing sites was analyzed in a collection of natural field isolates from different rice varieties grown in eight tungro-endemic sites of the Philippines. Total DNA extracts from 345 isolates were digested with EcoRV restriction enzyme and hybridized with a full-length probe of RTBV, a procedure shown in preliminary experiments capable of revealing high levels of polymorphism in RTBV field isolates. In the total population, 17 distinct EcoRV-based genome profiles (genotypes) were identified and used as indicators for virus diversity. Distinct sets of genotypes occurred in Isabela and North Cotabato provinces suggesting a geographic isolation of virus populations. However, among the sites in each province, there were few significant differences in the genotype compositions of virus populations. The number of genotypes detected at a site varied from two to nine with a few genotypes dominating. In general the isolates at a site persisted from season to season indicating a genetic stability for the local virus population. Over the sampling time, IRRI rice varieties, which have green leafhopper resistance genes, supported similar virus populations to those supported by other varieties, indicating that the variety of the host exerted no apparent selection pressures. Insect transmission experiments on selected RTBV field isolates showed that dramatic shifts in genotype and phenotype distributions can occur in response to host /environmental shifts.

Source apportionment of fine particles at a suburban site in Queensland, Australia

Airborne fine particles were collected at a suburban site in Queensland, Australia between 1995 and 2003. The samples were analysed for 21 elements, and Positive Matrix Factorisation (PMF), Preference Ranking Organisation METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) were applied to the data. PROMETHEE provided information on the ranking of pollutant levels from the sampling years while PMF provided insights into the sources of the pollutants, their chemical composition, most likely locations and relative contribution to the levels of particulate pollution at the site. PROMETHEE and GAIA found that the removal of lead from fuel in the area had a significant impact on the pollution patterns while PMF identified 6 pollution sources including: Railways (5.5%), Biomass Burning (43.3%), Soil (9.2%), Sea Salt (15.6%), Aged Sea Salt (24.4%) and Motor Vehicles (2.0%). Thus the results gave information that can assist in the formulation of mitigation measures for air pollution.

Is a mango just a mango? Testing within-fruit oviposition site choice and larval performance of a highly polyphagous fruit fly

For fruit flies, fully ripe fruit is preferred for adult oviposition and is superior for offspring performance over unripe or ripening fruit. Because not all parts of a single fruit ripen simultaneously, the opportunity exists for adult fruit flies to selectively choose riper parts of a fruit for oviposition and such selection, if it occurs, could positively influence offspring performance. Such fine scale host variation is rarely considered in fruit fly ecology, however, especially for polyphagous species which are, by definition, considered to be generalist host users. Here we study the adult oviposition preference/larval performance relationship of the Oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), a highly polyphagous pest species, at the “within-fruit” level to see if such a host use pattern occurs. We recorded the number of oviposition attempts that female flies made into three fruit portions (top, middle and bottom), and larval behavior and development within different fruit portions for ripening (color change) and fully-ripe mango, Mangifera indica L. (Anacardiaceae). Results indicate that female B. dorsalis do not oviposit uniformly across a mango fruit, but lay most often in the top (i.e., stalk end) of fruit and least in the bottom portion, regardless of ripening stage. There was no evidence of larval feeding site preference or performance (development time, pupal weight, percent pupation) being influenced by fruit portion, within or across the fruit ripening stages. There was, however, a very significant effect on adult emergence rate from pupae, with adult emergence rate from pupae from the bottom of ripening mango being approximately only 50% of the adult emergence rate from the top of ripening fruit, or from both the top and bottom of fully-ripe fruit. Differences in mechanical (firmness) and chemical (total soluble solids, titratable acidity, total non-structural carbohydrates) traits between different fruit portions were correlated with adult fruit utilisation. Our results support a positive adult preference/offspring performance relationship at within-fruit level for B. dorsalis. The fine level of host discrimination exhibited by B. dorsalis is at odds with the general perception that, as a polyphagous herbivore, the fly should show very little discrimination in its host use behavior.

A site selection process for environmental offsetting purposes in Queensland

A method of selecting land in any region of Queensland for offsetting purposes is devised, employing uniform standards. The procedure first requires that any core natural asset lands, Crown environmental lands, prime urban and agricultural lands, and highly contentious sites in the region be eliminated from consideration. Other land is then sought that is located between existing large reservations and the centre of greatest potential regional development/disturbance. Using the criteria of rehabilitation (rather than preservation) plus proximity to those officially defined Regional Ecosystems that are most threatened, adjacent sites that are described as ‘Cleared’ are identified in terms of agricultural land capability. Class IV lands – defined as those ‘which may be safely used for occasional cultivation with careful management’,2 ‘where it is favourably located for special usage’,3 and where it is ‘helpful to those who are interested in industry or regional planning or in reconstruction’4 – are examined for their appropriate area, for current tenure and for any conditions such as Mining Leases that may exist. The positive impacts from offsets on adjoining lands can then be designed to be significant; examples are also offered in respect of riparian areas and of Marine Parks. Criteria against which to measure performance for trading purposes include functional lift, with other case studies about this matter reported separately in this issue. The procedure takes no account of demand side economics (financial additionality), which requires commercial rather than environmental analysis.

The low-affinity site of the β1-adrenoceptor and its relevance to cardiovascular pharmacology

β-Adrenoceptor blocking agents (β-blockers) that at low concentrations antagonize cardiostimulant effects of catecholamines, but at high concentrations also cause cardiostimulation, have been appearing since the late 1960s. These cardiostimulant β-blockers, coined non-conventional partial agonists, antagonize the effects of catecholamines through a high-affinity site (β1HAR), but cause cardiostimulation mainly through a low-affinity site (β1LAR) of the myocardial β1-adrenoceptor. The experimental non-conventional partial agonist (−)-CGP12177 increases cardiac L-type Ca2+ current density and Ca2+ transients, shortens action potential duration but augments action potential plateau, increases heart rate and force, as well as causes arrhythmic Ca2+ transients and arrhythmic cardiocyte contractions. Other β-blockers, which do not cause cardiostimulation, consistently have lower affinity for β1LAR than β1HAR. These sites were verified and the cardiac pharmacology of non-conventional partial agonists confirmed on recombinant β1-adrenoceptors and on β1-adrenoceptors overexpressed into the heart. A targeted mutation of Asp138 to Glu138 virtually abolished the pharmacology of β1HAR but left intact the pharmacology of β1LAR. Non-conventional partial agonists may be beneficial for the treatment of peripheral autonomic neuropathy but probably due to their arrhythmic propensities, may be harmful for the treatment of chronic heart failure.

Obesity screening for young Japanese males and females using skin fold measurements : the classification revisited

Anthropometric assessment is a simple, safe, and cost-efficient method to examine the health status of individu-als. The Japanese obesity classification based on the sum of two skin folds (Σ2SF) was proposed nearly 40 years ago therefore its applicability to Japanese living today is unknown. The current study aimed to determine Σ2SF cut-off values that correspond to percent body fat (%BF) and BMI values using two datasets from young Japa-nese adults (233 males and 139 females). Using regression analysis, Σ2SF and height-corrected Σ2SF (HtΣ2SF) values that correspond to %BF of 20, 25, and 30% for males and 30, 35, and 40% for females were determined. In addition, cut-off values of both Σ2SF and HtΣ2SF that correspond to BMI values of 23 kg/m2, 25 kg/m2 and 30 kg/m2 were determined. In comparison with the original Σ2SF values, the proposed values are smaller by about 10 mm at maximum. The proposed values show an improvement in sensitivity from about 25% to above 90% to identify individuals with ≥20% body fat in males and ≥30% body fat in females with high specificity of about 95% in both genders. The results indicate that the original Σ2SF cut-off values to screen obese individuals cannot be applied to young Japanese adults living today and modification is required. Application of the pro-posed values may assist screening in the clinical setting.

Social network market : storytelling on a Web 2.0 original literature site

This article looks at a Chinese Web 2.0 original literature site, Qidian, in order to show the coevolution of market and non-market initiatives. The analytic framework of social network markets (Potts et al., 2008) is employed to analyse the motivations of publishing original literature works online and to understand the support mechanisms of the site, which encourage readers’ willingness to pay for user-generated content. The co-existence of socio-cultural and commercial economies and their impact on the successful business model of the site are illustrated in this case. This article extends the concept of social network markets by proposing the existence of a ripple effect of social network markets through convergence between PC and mobile internet, traditional and internet publishing, and between publishing and other cultural industries. It also examines the side effects of social network markets, and the role of market and non-market strategies in addressing the issues.

Assigning metabolic equivalent (MET) values to the 2002 Census Occupational Classification System

Background: The Current Population Survey (CPS) and the American Time Use Survey (ATUS) use the 2002 census occupation system to classify workers into 509 separate occupations arranged into 22 major occupational categories. Methods: We describe the methods and rationale for assigning detailed MET estimates to occupations and present population estimates (comparing outputs generated by analysis of previously published summary MET estimates to the detailed MET estimates) of intensities of occupational activity using the 2003 ATUS data comprised of 20,720 respondents, 5,323 (2,917 males and 2,406 females) of whom reported working 6+ hours at their primary occupation on their assigned reporting day. Results: Analysis using the summary MET estimates resulted in 4% more workers in sedentary occupations, 6% more in light, 7% less in moderate, and 3% less in vigorous compared to using the detailed MET estimates. The detailed estimates are more sensitive to identifying individuals who do any occupational activity that is moderate or vigorous in intensity resulting in fewer workers in sedentary and light intensity occupations. Conclusions: Since CPS/ATUS regularly captures occupation data it will be possible to track prevalence of the different intensity levels of occupations. Updates will be required with inevitable adjustments to future occupational classification systems.

Overview of the INEX 2010 XML mining track : clustering and classification of XML documents

The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problems and new challenges of the emerging field of mining semi-structured documents, and (2) studying and assessing the potential of Machine Learning (ML) techniques for dealing with generic ML tasks in the structured domain, i.e., classification and clustering of semi-structured documents. This track has run for six editions during INEX 2005, 2006, 2007, 2008, 2009 and 2010. The first five editions have been summarized in previous editions and we focus here on the 2010 edition. INEX 2010 included two tasks in the XML Mining track: (1) unsupervised clustering task and (2) semi-supervised classification task where documents are organized in a graph. The clustering task requires the participants to group the documents into clusters without any knowledge of category labels using an unsupervised learning algorithm. On the other hand, the classification task requires the participants to label the documents in the dataset into known categories using a supervised learning algorithm and a training set. This report gives the details of clustering and classification tasks.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.